Zobrazeno 1 - 10
of 110
pro vyhledávání: '"Dmitri B. Chklovskii"'
Autor:
Siavash Golkar, Jules Berman, David Lipshutz, Robert Mihai Haret, Tim Gollisch, Dmitri B. Chklovskii
Publikováno v:
Physical Review Research, Vol 6, Iss 1, p 013111 (2024)
This article is part of the Physical Review Research collection titled Physics of Neuroscience. To generate actions in the face of physiological delays, the brain must predict the future. Here we explore how prediction may lie at the core of brain fu
Externí odkaz:
https://doaj.org/article/1fd16193c86348258b614d3fc15e918e
Autor:
Jong-Cheol eRah, Erhan eBas, Jennifer eColonell, Yuriy eMishchenko, Bill eKarsh, Richard D. Fetter, Eugene W. Myers, Dmitri B. Chklovskii, Karel eSvoboda, Timothy D. Harris, John T.R. Isaac
Publikováno v:
Frontiers in Neural Circuits, Vol 7 (2013)
The subcellular locations of synapses on pyramidal neurons strongly influences dendritic integration and synaptic plasticity. Despite this, there is little quantitative data on spatial distributions of specific types of synaptic input. Here we use ar
Externí odkaz:
https://doaj.org/article/144dc6f156e84e5fb89485927dfed5d5
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 2, p e1010864 (2023)
To adapt to their environments, animals learn associations between sensory stimuli and unconditioned stimuli. In invertebrates, olfactory associative learning primarily occurs in the mushroom body, which is segregated into separate compartments. With
Externí odkaz:
https://doaj.org/article/b49fe217b9774a06909b4bc0f6759d90
Autor:
Shanshan Qin, Shiva Farashahi, David Lipshutz, Anirvan M. Sengupta, Dmitri B. Chklovskii, Cengiz Pehlevan
Publikováno v:
Nature Neuroscience. 26:339-349
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1a69eac1416714ad5f4e80cd5cb4f4ca
https://doi.org/10.1038/s41593-022-01225-z
https://doi.org/10.1038/s41593-022-01225-z
Publikováno v:
Biological Cybernetics. 116:557-568
An important problem in neuroscience is to understand how brains extract relevant signals from mixtures of unknown sources, i.e., perform blind source separation. To model how the brain performs this task, we seek a biologically plausible single-laye
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::71a38c86145437f85c32b2c74cb54673
https://doi.org/10.1007/s00422-022-00943-8
https://doi.org/10.1007/s00422-022-00943-8
Autor:
Andrea Giovannucci, Johannes Friedrich, Pat Gunn, Jérémie Kalfon, Brandon L Brown, Sue Ann Koay, Jiannis Taxidis, Farzaneh Najafi, Jeffrey L Gauthier, Pengcheng Zhou, Baljit S Khakh, David W Tank, Dmitri B Chklovskii, Eftychios A Pnevmatikakis
Publikováno v:
eLife, Vol 8 (2019)
Advances in fluorescence microscopy enable monitoring larger brain areas in-vivo with finer time resolution. The resulting data rates require reproducible analysis pipelines that are reliable, fully automated, and scalable to datasets generated over
Externí odkaz:
https://doaj.org/article/d7b31fa323ac445a92728f820909d1e0
Publikováno v:
Neural Computation. 34:891-938
The brain must extract behaviorally relevant latent variables from the signals streamed by the sensory organs. Such latent variables are often encoded in the dynamics that generated the signal rather than in the specific realization of the waveform.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12cc8896b4f464626116e6e47b761511
https://doi.org/10.1162/neco_a_01476
https://doi.org/10.1162/neco_a_01476
To adapt to their environments, animals learn associations between sensory stimuli and unconditioned stimuli. In invertebrates, olfactory associative learning primarily occurs in the mushroom body, which is segregated into separate compartments. With
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e9c54680cbda9f3d8b98fcecc3ef62b
https://doi.org/10.1101/2022.09.23.508775
https://doi.org/10.1101/2022.09.23.508775
Publikováno v:
Neural Computation. 33:2309-2352
Cortical pyramidal neurons receive inputs from multiple distinct neural populations and integrate these inputs in separate dendritic compartments. We explore the possibility that cortical microcircuits implement canonical correlation analysis (CCA),
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3a41458988d838233e7486fac865cb1b
https://doi.org/10.1162/neco_a_01414
https://doi.org/10.1162/neco_a_01414
Autor:
Shin-ya Takemura, Aljoscha Nern, Dmitri B Chklovskii, Louis K Scheffer, Gerald M Rubin, Ian A Meinertzhagen
Publikováno v:
eLife, Vol 6 (2017)
Analysing computations in neural circuits often uses simplified models because the actual neuronal implementation is not known. For example, a problem in vision, how the eye detects image motion, has long been analysed using Hassenstein-Reichardt (HR
Externí odkaz:
https://doaj.org/article/2d708527749040ec844a7ecea1e6c88e